Weed Research Articles

The Effect of Early Control of Weeds Associated with the Maize Crop Using Herbicides

A field experiment was conducted at the Field Crops Research Station in AL-Ghalbiea, Diyala Governorate, Iraq, during the 2022 fall season, in clay soil. This study aimed to determine the best pesticide and the most appropriate concentration to control weeds associated with the maize crop in the field. The results obtained showed that the herbicides atrazine and guradian were suitable control products. When the herbicide atrazine was used at the concentration of 4 L/ha, the number of grains/ear and total yield reached 532.83/ear and 9.90 ton/ha, respectively. Whereas at the concentration of 2 L/ha, the 1000 grains weight reached 260.41 g. The use of guradian herbicide significantly increased the ear length and reached 21.41cm. Best results were obtained when both herbicides were combined in one treatment. Keywords: Maize, guradian, atrazine, herbicides.

Integrated analysis of transcriptome and metabolome revealed clomazone biodegradation in maize seedlings.

Integrated analysis of transcriptome and metabolome revealed clomazone biodegradation in maize seedlings.

Weed-crop dataset in precision agriculture: Resource for AI-based robotic weed control systems.

Weed-crop dataset in precision agriculture: Resource for AI-based robotic weed control systems.

Weed Suppression Potential of Ailanthus altissima Compost: Effects on Germination and Emergence

The Tree of Heaven (Ailanthus altissima (Mill.) Swingle), originally from Southeast Asia, is considered an invasive alien plant in many countries. It produces a strong allelochemical called ailanthone, and this phytotoxic quassinoid inhibits the germination of seeds and/or suppresses the growth of other plants. This study aimed to determine the applicability of plant biomass of the Ailanthus as a raw material to prepare various compost types. The compost treatments were composed of the biomass of A. altissima alone, the biomass of A. altissima+chicken manure, and the biomass of A. altissima+cattle manure. Weed seeds in the mixtures were kept for 7, 14, 21, and 28 days in the composts during the summer and autumn seasons, and the effect of these durations on the viability of the weed seeds was determined by a 28-day petri experiment. The percentage of decayed weed seeds (DSP) placed in the compost increased over time. The decayed seed percentage for Sorghum halepense (L.) Pers. (Johnson grass) in summer-prepared compost was higher than that in autumn-prepared composts, whereas seasonal differences were insignificant for Convolvulus arvensis L. (Field bindweed). Additionally, increasing mulch thickness reduced weed emergence, indicating that a mulch layer of at least 5 cm is necessary for effective weed control.

Discovery of novel herbicidal cyclic keto-enol derivatives containing a pyridazinone moiety and their structure-activity relationship studies on weeds.

Acetyl-coenzyme A carboxylase (ACCase) is one of the most important enzymes involved in the biosynthesis of fatty acids in both plants and animals, and its inhibitors are widely used to control gramineous plants or sucking pests in crop fields. Phenyl-substituted cyclic keto-enols (CKEs) are known as a chemical class inhibiting ACCase, and several compounds are commercially available as herbicides or insecticides. We synthesized a new series of phenyl-substituted CKEs containing a pyridazinone moiety and examined the structure-activity relationship (SAR) based on herbicidal activity. We found that the methyl group at the 2 position of the pyridazinone ring significantly contributes to herbicidal efficacy. Similarly, we revealed that a methyl group at the 6 position of the pyridazinone ring is critical for exerting high herbicidal activity on both grass weeds and broadleaf weeds. Additionally, compounds with ethyl groups at the ortho position of the phenyl ring showed improved herbicidal activity, especially against grass weeds. The ACCase inhibition assay results showed good correlations with the SAR of the pot tests. Several optimized compounds, based on herbicidal activity, demonstrated high herbicidal efficacy against not only grass weeds but also broadleaf weeds, causing characteristic bleaching symptoms. Phenyl-substituted CKE derivatives containing a pyridazinone moiety have a broad weed control spectrum and likely possess multiple modes of action. These features make these compounds useful as tools for effectively controlling a variety of weeds, including resistant weeds. © 2025 Society of Chemical Industry.

The usage of imidazolinone-tolerant maize in maize-soybean strip intercropping greatly facilitates weed control

The strip intercropping system is one of the important production strategy for maize and soybean. However, it faces significant yield losses due to the lack of safe and effective postemergence herbicides compatible with both crops. In this context, the introduction of imidazolinone-tolerant maize presents a potential solution, yet the associated crop traits, yield outcomes, herbicidal efficacy, and economic impacts have not been thoroughly evaluated. Therefore, this study systematically compares two weed control strategies in maize-soybean strip intercropping system: non-segregated weeding (NSW), which uses imidazolinone-tolerant maize to allow for shared herbicide application, and segregated weeding (SW), which employs a dual-system sprayer for separate herbicide treatments for maize and soybean. A control group with no weed control (NW) was also included to compare the results across treatments. Our results revealed that the differences in plant height and stem diameter between maize and soybean were not significant between NSW and SW, though both were substantially lower compared to their respective monocultures. Compared to SW, the NSW treatment increased the leaf area index, total dry matter accumulation, and grain yield of soybean by 33%, 17%, and 79%, respectively. For maize, these parameters were marginally higher but not significant, indicating that the NSW treatment benefited soybean growth and yield more than maize in maize-soybean strip intercropping system. Overall, maize and soybean under SW and NSW achieved land equivalent ratios of 0.96 and 0.99 for maize, and 0.40 and 0.80 for soybean, respectively, suggesting that the NSW strategy provided better weed control and allowed for more efficient land use for both maize and soybean. Specifically, in terms of weed suppression, NSW outperformed SW, with the number and fresh weight of weeds (Gramineae, Broadleaf, Cyperaceous) reduced to 16% and 20% of those in SW, and to 5% and 4% of those in NW, respectively. Moreover, NSW increased weeding speed by fivefold, reduced herbicide and spraying costs by $37.05 USD ha-1, and enhanced net benefits by 58%, reaching $3414.12 USD ha-1. These findings demonstrate that NSW, based on imidazolinone-tolerant maize, offers a more convenient, economical, and efficient weed management strategy for maize-soybean strip intercropping system.

Biomaterial Geotextile Berbahan Biomassa untuk Meningkatkan Produktivitas Pertanian di Desa Sidorejo Kabupaten Bojonegoro

This community service program aims to develop sustainable geotextiles made from local biomass. It involves training farmers in their production as an effort to reduce plastic use, improve soil health, and increase yields of papaya and chili crops. This community service implementation uses a participatory approach targeting farmers who are members of the "Karya Tani" farmer group in Desa Sidorejo, Bojonegoro Regency, East Java, with a total of 25 participants. The results of this service indicate that plastic mulch can be replaced with geotextiles made from local biomass in maintaining soil moisture, weed control, sunlight absorption, and water management. The best results were obtained from coconut coir geotextiles compared to straw, yielding 500 kg of papaya harvest from a 0.25-hectare plantation. Ultimately, this community development project aims to promote sustainable agriculture, empower rural communities, and contribute to a circular economy.

Honey Plants of Artvin (Türkiye)

In this study, information about nectar and pollen plants crucial in beekeeping activities in Artvin province is presented. The aim of the research is to identify, introduce, and highlight the floristic richness of honey plants in the vicinity of Artvin province for beekeeping purposes. Through the examination of related studies, 789 plant taxa belonging to 355 genera and 91 families that honey bees (Apis mellifera) can benefit from were identified. 90 taxon were determined only within the scope of this study. The scientific and Turkish names, habitats, and active flowering periods important for bees were provided for these identified taxa. Lamiaceae are the largest families represented by 78 taxa each, followed by Rosaceae with 65 taxa, Asteraceae with 63 taxa, Fabaceae with 58 taxa and Apiaceae with 33 taxa. Moreover, it was determined that 600 out of the 789 plant taxa that can be used as nectar and pollen sources. This study provides information about the distribution in Artvin province, their respective families, Latin and Turkish names, districts where they are found, habitats, and active flowering periods for some plants crucial for beekeeping. Due to the absence of chemical fertilizers, herbicides, and other chemical substances for weed and pest control, the region holds significant potential for organic honey production. The high-quality organic honey produced in the region is in demand nationwide, enabling beekeepers to generate substantial income from honey production.

Influence of Integrated Weed Management and Nitrogen Levels on Nutrient Dynamics, Yield, and Quality of Sesame (Sesamum indicum L.) under Semi-arid Conditions

A field experiment was conducted during the kharif season, to evaluate the effect of integrated weed-management practices and nitrogen levels on nutrient content, uptake, nitrogen-use efficiency, and seed quality of sesame. The trial followed a factorial randomized block design comprising seven weed-management strategies and three nitrogen rates (0, 20, and 40 kg N ha⁻¹). Results revealed that the application of imazethapyr at 0.15 kg ha-1 fb one hand-weeding at 30 DAS significantly improved crop growth parameters, nutrient content (N, P, K), and seed yield (855 kg ha-1), while also minimizing nutrient depletion by weeds. This treatment was statistically on par with two hand-weedings at 20 and 40 DAS. Nitrogen application up to 40 kg ha-1 significantly increased total nutrient uptake (N: 50.44 kg ha-1, P: 9.76 kg ha-1, K: 83.74 kg ha-1), seed protein (17.31%), and oil content (43.39%). However, it also led to higher nutrient removal by weeds under sub-optimal weed control. The findings show that combining effective weed suppression strategies with moderate nitrogen application improves yield, quality, and nutrient-use efficiency of sesame in semi-arid, loamy-sandy soils.

Precision Weed Control Using Unmanned Aerial Vehicles and Robots: Assessing Feasibility, Bottlenecks, and Recommendations for Scaling

Weeds cause significant yield and economic losses by competing with crops and increasing production costs. Compounding these challenges are labor shortages, herbicide resistance, and environmental pollution, making weed management increasingly difficult. In response, precision weed control (PWC) technologies, such as robots and unmanned aerial vehicles (UAVs), have emerged as innovative solutions. These tools offer farmers high precision (±1 cm spatial accuracy), enabling efficient and sustainable weed management. Herbicide spraying robots, mechanical weeding robots, and laser-based weeders are deployed on large-scale farms in developed countries. Similarly, UAVs are gaining popularity in many countries, particularly in Asia, for weed monitoring and herbicide application. Despite advancements in robotic and UAV weed control, their large-scale adoption remains limited. The reasons for this slow uptake and the barriers to widespread implementation are not fully understood. To address this knowledge gap, our review analyzes 155 articles and provides a comprehensive understanding of PWC challenges and needed interventions for scaling. This review revealed that AI-driven weed mapping in robots and UAVs struggles with data (quality, diversity, bias) and technical (computation, deployment, cost) barriers. Improved data (collection, processing, synthesis, bias mitigation) and efficient, affordable technology (edge/hybrid computing, lightweight algorithms, centralized computing resources, energy-efficient hardware) are required to improve AI-driven weed mapping adoption. Specifically, robotic weed control adoption is hindered by challenges in weed recognition, navigation complexity, limited battery life, data management (connectivity), fragmented farms, high costs, and limited digital literacy. Scaling requires advancements in weed detection and energy efficiency, development of affordable robots with shared service models, enhanced farmer training, improved rural connectivity, and precise engineering solutions. Similarly, UAV adoption in agriculture faces hurdles such as regulations (permits), limited payload and battery life, weather dependency, spray drift, sensor accuracy, lack of skilled operators, high initial and operational costs, and absence of standardized protocol. Scaling requires financing (subsidies, loans), favorable regulations (streamlined permits, online training), infrastructure development (service providers, hiring centers), technological innovation (interchangeable sensors, multipurpose UAVs), and capacity building (farmer training programs, awareness initiatives).

Impact of Integrated Herbicide Hand Weeding Practices and Nitrogen Rates Enhance Weed Control and Seed Yield of Sesame (Sesamum indicum L.) under Semi Arid, Loamy Sandy Soils

A field experiment was conducted on loamy‑sandy soil during the kharif season. The factorial RBD trial comprised seven weed‑management treatments: weedy check; one hand‑weeding (HW) at 20 DAS; two HW at 20 & 40 DAS; alachlor 1.5 kg ha-1; alachlor 1.5 kg ha-1 + HW 30 DAS; imazethapyr 0.15 kg ha-1; and imazethapyr 0.15 kg ha-1 + HW 30 DAS, combined with three nitrogen rates (0, 20, 40 kg N ha-1), each treatment replicated thrice. Pre‑emergence imazethapyr 0.15 kg ha-1 + one HW at 30 DAS and two HW at 20 and 40 DAS gave the greatest weed suppression, lowering weed density and dry matter by approximately 82 % at harvest and achieving the highest weed‑control efficiency among all treatments. The imazethapyr + HW package also produced the tallest plant (143.05 cm) and the maximum seed yield (855 kg ha-1), significantly surpassing all other weed‑control options. The integrated weed management practice involving the application of Imazethapyr @ 1.5 kg ha-1 + hand weeding at 30 DAS proved to be the most effective in suppressing weed growth. Nitrogen nutrition further enhanced crop performance: raising the dose to 40 kg N ha-1 delivered the tallest plants both at 50 DAS and harvest and the highest mean seed yield (787 kg ha-1), demonstrating that adequate N amplifies the benefits of effective weed management in sesame.

Effects of weed management strategy on weed dynamics and its repercussion on productivity of Indian mustard

A field experiment was conducted during rabi season of 2022-23, at Banda University of Agriculture and Technology, Banda, Uttar Pradesh to study the efficacy of herbicides on weed dynamics and productivity of Indian mustard [Brassica juncea (L.) Czern & Coss]. Experiment was laid out in Randomized Block Design with eight treatments and replicated four times. Experimental crop of mustard was infested with several weeds viz. Cyperus rotundus, Cynodon dactylon, Anagalis arvensis, Chenopodium album, Dacaus carota,Rumex crispus.All the cultural and herbicidal treatments effectively reduced the dry weight of weeds by 60.8-61.5 % compared to the weedy check. Weed control efficiency at 75 DAS were in the range of 36.9 to 61.5 per cent. Yield loss due to weeds recorded 24.1%, when weeds remain unmanaged in field. The highest seed yield 1.84t ha-1obtained under weed-free conditions. Among herbicides, Pendimethalin 30 EC 1000g a.i. ha1 PE fb (Propaquizafop 5% + oxyflourfen 12% w/w EC (ready-mix) @ 875g a.i. ha-1 PoE, recorded significantly higher seed yield of 1.7 t ha-1 and net returns of Rs.73604 ha-1. The dose of propaquizafop 5% + oxyflourfen 12% w/w EC (ready-mix) @ 875g a.i. ha-1 post emergence application had phytotoxic effect on crop.

Effect of Diquat on gut health: molecular mechanisms, toxic effects, and protective strategies.

Diquat is a widely used bipyridyl herbicide that is extensively applied in agricultural production and water management due to its high efficacy in weed control. However, its environmental persistence and the toxic effects it induces have raised widespread concern. Studies show that Diquat primarily enters the body through the digestive tract, leading to poisoning. The core mechanism of its toxicity involves reactive oxygen species (ROS)-induced oxidative stress, which not only directly damages the intestinal barrier function but also exacerbates inflammation and systemic toxicity by disrupting the balance of the gut microbiota and the normal production of metabolic products. This review systematically summarizes the physicochemical properties of Diquat, with a focus on analyzing the mechanisms by which it damages the gut tissue structure, barrier function, and microbiota after digestive tract exposure. The aim is to provide theoretical support for a deeper understanding of Diquat's toxic mechanisms and its digestive tract-centered toxic characteristics, laying a scientific foundation for the development of effective interventions and protective strategies against its toxicity.

Fabricating supramolecular pre-emergence herbicide CPAM-BPyHs for farming herbicide-resistant rice

Controlling weeds before their emergence is crucial for minimizing their impacts on crop yield and quality. Bipyridyl herbicides (BPyHs), a class of highly effective and broad-spectrum herbicides, cannot be used as pre-emergence herbicides because they can be absorbed and inactivated by negatively charged soil after application. Here, we design and fabricate an adsorbed-but-active supramolecular pre-emergence herbicide consisting of cationic polyacrylamide and bipyridyl herbicides (CPAM-BPyHs). CPAM is a positively charged polymer. It can preferentially bind to soil particles and shift their electric potential to a more positive value. Thus, it prevents not only runoff but also inactivation of BPyHs. We also develop a BPyHs-resistant rice line by mutation of the gene encoding L-type amino acid transporter 5 (OsLAT5). Field trial results show that the weed control efficiency of CPAM-diquat for direct-seeded herbicide-resistant rice line exceeds 90%. The herbicidal activity can maintain up to one month with only one application. This work offers a method for rice weed control and provides insights into the design of pesticides to prevent soil inactivation and runoff.

CRISPR/Cas9-Mediated Knockout of the White Gene in Agasicles hygrophila.

Agasicles hygrophila is the most effective natural enemy for the control of the invasive weed Alternanthera philoxeroides (Mart.) Griseb. However, research on the gene function and potential genetic improvement of A. hygrophila is limited due to a lack of effective genetic tools. In this study, we employed the A. hygrophila white (AhW) gene as a target gene to develop a CRISPR/Cas9-based gene editing method applicable to A. hygrophila. We showed that injection of Cas9/sgRNA ribonucleoprotein complexes (RNPs) of the AhW gene into pre-blastoderm eggs induced genetic insertion and deletion mutations, leading to white eyes. Our results demonstrate that CRISPR/Cas9-mediated gene editing is possible in A. hygrophila, offering a valuable tool for studies of functional genomics and genetic improvement of A. hygrophila, which could potentially lead to more effective control of invasive weeds through the development of improved strains of this biocontrol agent. In addition, the white-eyed mutant strain we developed could potentially be useful for other transgenic research studies on this species.

Modified sprayer design for berry-producing farms

This article describes the experience of adjusting the technology of disease and insect control for protecting raspberry plantations under the conditions of a small-size berry-growing farm. The research aim was to develop a modular sprayer design that would meet the current environmental and economic requirements. Approaches to improving the ecological safety of berry plantation spraying are considered, in particular, by using the tunnel type of sprayers or charging the drops of working fl uid. Although being ecologically safe, spraying in the protected volume with the recovery of excess working liquid was shown to be unacceptable for small-size farms from the standpoint of economic effi ciency. Even under low-wind conditions, the pesticide spray on the windward side of the row form a continuous fi ne-dispersed cloud that penetrates through the fruit wall of raspberries. This eliminates the need to use a U-shaped boom. At the same time, the farm machinery operator is protected by turning the L-shaped boom by 180º to the leeward side in relation to the tractor each time the vehicle moves to the next inter-row spacing. The main object of weed control in raspberry plantations was found to be couch grass (Elymus repens), which is controlled by applying the Roundup herbicide at a dose of 5 L/ha. A special design for the herbicide boom, which can be additionally equipped with a sprayer, was proposed. Stinging nettle can be eff ectively controlled by treating its local areas with the Agritox herbicide using a backpack sprayer during periods preceding the onset of raspberry vegetation. The working solution is prepared at the rate of 1.2 L of herbicide per 200 L of water. Since farms, in addition to raspberries, may produce black currants and garden strawberries, the sprayer should be additionally equipped with a transverse horizontal boom with four levels of installation height.

Glyphosate resistance and EPSPS gene amplification confirmed in a waterhemp (Amaranthus tuberculatus) biotype from Connecticut

AbstractWaterhemp (Amaranthus tuberculatus) is an economically important broadleaf weed that threatens corn and soybean production across the United States. A waterhemp biotype (CT_Res [resistant biotype from Connecticut]) surviving multiple glyphosate applications was identified from a corn field in Connecticut (CT). Greenhouse and laboratory studies were conducted to (1) confirm glyphosate resistance in CT_Res waterhemp biotype and (2) investigate if the glyphosate resistance in CT_Res biotype is due to target‐site‐based mechanism. Dose‐response studies indicated that CT_Res biotype was 5.8‐fold more resistant to glyphosate compared to a known susceptible biotype (NE_Sus) from Nebraska. No point mutation was detected at Pro102 or Thr106 positions in the EPSPS gene of the CT_Res biotype. The quantitative polymerase chain reaction assays revealed that one of the three CT_Res waterhemp plants had 3.5‐fold higher EPSPS gene copy number (relative to the housekeeping CPS gene), whereas the other two plants did not reveal EPSPS gene amplification. Obviously, the EPSPS gene amplification partially explains glyphosate resistance in newly identified glyphosate‐resistant waterhemp biotype from CT, indicating that alternative mechanisms might exist. This research reports the first case of glyphosate resistance and EPSPS gene amplification in waterhemp from Connecticut and highlights the need for adoption of diversified weed control strategies to prevent its further spread.

Constraints and Suggestions for Improving Technology Adoption in Chickpea Cultivation under Cluster Front Line Demonstration (CFLD) Program in Arid Region

The field study was conducted in Bikaner district of Rajasthan to identify the problems encountered by farmers in the adoption of chickpea cultivation technologies under the Cluster Front Line Demonstration (CFLD) program and to gather their suggestions for improving future interventions. A total of 200 farmers, comprising 100 beneficiary and 100 non-beneficiary farmers, were selected using proportionate random sampling from Bikaner and Kolayat tehsils. Data were collected through structured interviews and analyzed to assess input, financial, technical, environmental, and marketing constraints. Results indicated that major input-related problems among overall farmers were the unavailability of recommended chemicals for plant protection and fertilizers at the time of sowing. Financial challenges included the high cost of labor and fertilizers. Technical constraints mainly involved complications in weed control practices and lack of knowledge regarding seed rates and plant protection measures. Environmental problems were largely attributed to abrupt temperature increases during maturity and frost injury. Marketing issues such as lower prices at harvest and lack of storage facilities were also prominent. Farmers suggested that timely availability of plant protection chemicals and fertilizers, provision of subsidized plant protection equipment, and training on improved agronomic practices could significantly enhance the effectiveness of CFLD programs. The findings highlighted the need for strengthening input delivery systems, improving technical training, and enhancing market linkages to foster better adoption of chickpea technologies in arid regions like Bikaner.

Role of Planting Patterns and Weed Control Methods on Growth and Development of Fennel (Foeniculum vulgare Mill.)

Background: The field experiment was conducted at the Research Farm of Lovely Professional University, Phagwara, Punjab, India during Rabi season 2023-24 to find out the role of planting patterns and weed control methods on growth and development of Fennel (Foeniculum vulgare Mill.). Methods: The experiment was laid out in split plot design with three replications. In main plots, four planting patterns i.e. two rows per bed (90 cm), ridge sowing (45 cm), flat sowing (45 cm) f.b. earthing up, flat sowing (45 cm) and in sub plots, four weed control treatments, i.e. black plastic mulch, white plastic mulch, hand weeding f.b. straw mulch (5 t ha-1) and unweeded (control) were kept. Result: The results of the study revealed that weed count and weed dry matter in flat sowing (45 cm) f.b. earthing up was significantly less than flat sowing (45 cm) and among weed control treatments, black plastic mulch recorded significantly less weed count and weed dry matter than other treatments. Plant height, dry matter per plant, seed yield and biological yield were found significantly higher in flat sowing (45 cm) f.b. earthing up as compared to flat sowing (45 cm). Black plastic mulch and white plastic mulch recorded significantly higher growth and yield parameters than unweeded (control). The seed yield in flat sowing (45 cm) f.b. earthing up was 33.5% higher than flat sowing (45 cm). Black plastic mulch recorded 85.28% higher seed yield over control, which was significantly more as compared to all other treatments. It was concluded that the combination of flat sowing (45 cm) f.b. earthing up and black plastic mulch gave better results as compared to all other treatments.

Revolutionizing Agriculture Machine and Deep Learning Solutions for Enhanced Crop Quality and Weed Control

Deep learning is the nucleus in machine learning discipline which uses knowledge representation of learning. Learning can be supervised or unsupervised. Much Deep learning architecture are available which includes deep belief networks, deep neural networks and recurrent neural networks of which it has been applied to most of the fields. The commonly used applications of deep learning are vision related, audio, video, language processing, social media, medical, game and many more programs where they have produced promising accurate results comparable to and in few cases superior to human experts. Smart agriculture is an area that can benefit from the latest advances in expert systems. One of the objective is to remove the weeds by reducing the use of herbicides used, the risk of pollution of crop and water. The image of crop field is given as input training examples. By using the extracted feature, the images with weeds are detected and classified. A deep learning model is developed using convolution neural network to detect weeds with a good accuracy so that the model could be used to detect the weeds in the cucumber crop field ina shorter time.